Job Title: AI/ML Engineer – Data
Science, Generative AI & Computer
Vision
Experience: 3–6 Years
Location: Pune (Chakan & Mundhwa) / Mumbai (Kandivali)
Job Overview
We are seeking a highly skilled AI/ML Engineer with expertise in Machine Learning, Deep
Learning, Computer Vision, NLP, Generative AI, and Large Language Models (LLMs) to
design, develop, and deploy production-grade AI solutions. The ideal candidate will have
hands-on experience building scalable AI applications, Retrieval-Augmented Generation (RAG)
systems, AI agents, and computer vision models while integrating AI capabilities into enterprise
applications using modern MLOps and cloud technologies.
This role requires strong problem-solving skills, production-focused development experience,
and the ability to collaborate with cross-functional teams to deliver end-to-end AI solutions.
Key Responsibilities
AI/ML & Data Science
● Design, develop, train, evaluate, and deploy Machine Learning and Deep Learning
models for production environments.
● Build end-to-end ML pipelines including data collection, preprocessing, feature
engineering, model training, validation, deployment, and monitoring.
● Work with structured and unstructured datasets using Python and SQL.
● Optimize model performance through hyperparameter tuning, model evaluation, and
continuous monitoring.
● Build scalable AI solutions using FastAPI or Flask.
Generative AI & LLMs
● Design and implement production-grade Generative AI applications using Large
Language Models (LLMs).
● Build Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector
databases, and semantic search.
● Develop AI Agents and multi-agent workflows using frameworks such as:
○ LangChain
○ LangGraph
○ LlamaIndex
○ Haystack
○ Google ADK
● Implement prompt engineering, context management, model evaluation, and response
optimization.
● Integrate AI capabilities into enterprise applications through REST APIs and
microservices.
Computer Vision
● Design and deploy Computer Vision solutions for:
○ Image Classification
○ Object Detection (YOLO, Faster R-CNN, SSD)
○ Image Segmentation (U-Net, Mask R-CNN)
○ OCR & Document Understanding
○ Video Analytics
● Fine-tune Deep Learning and Vision Transformer models for production use cases.
● Optimize inference performance using ONNX, TensorRT, or similar optimization
frameworks.
Production AI & MLOps
● Deploy AI applications using Docker and Kubernetes.
● Build production-ready APIs using FastAPI or Flask.
● Implement model versioning, monitoring, CI/CD, and lifecycle management using
MLflow.
● Work with cloud AI services on AWS, Azure, or GCP (Vertex AI preferred).
● Monitor AI models for performance, drift, observability, and cost optimization.
Collaboration
● Work closely with Data Engineers, Backend Developers, Product Managers, and
Business Teams.
● Participate in architecture discussions and AI solution design.
● Research emerging AI technologies and recommend improvements.
Required Skills
● Programming
● Python
● SQL
● Machine Learning
● Deep Learning
● Computer Vision
● Generative AI
● AI Frameworks
● Data Processing
● APIs & Backend
● Databases
● DevOps & MLOps
● Cloud Platforms
Good to Have
● Experience with Multi-Agent AI systems
● Claude/OpenAI/Gemini APIs
● Azure OpenAI / AWS Bedrock / Vertex AI
● Databricks
● ONNX
● TensorRT
● Hugging Face
● Document AI
● Manufacturing AI
● Surveillance AI
● Retail AI
● Healthcare AI
● Reinforcement Learning
● Contributions to open-source AI/ML projects
● Cost optimization and AI observability tools
Soft Skills
● Excellent analytical and problem-solving abilities.
● Strong communication and stakeholder management skills.
● Self-motivated with a continuous learning mindset.
● Ability to work independently and collaboratively in cross-functional teams.
● Ownership of end-to-end AI solution delivery.
● Production-oriented mindset with focus on scalability, reliability, and business impact.
Preferred Qualifications
● Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science,
Machine Learning, or a related field.
● 3–6 years of hands-on experience in AI/ML, Data Science, Computer Vision, NLP, or
Generative AI.
● Experience building and deploying enterprise-scale AI solutions in production
environments.
